Publication date
2014Keyword
Botnet detection; Anomaly detection
; Network security
; Attack
; Defense
; Taxonomy
; Remote-control behavior
; Anomaly detection
; Command
; Dark
Peer-Reviewed
Yes
Metadata
Show full item recordAbstract
In recent years, the Internet has enabled access to widespread remote services in the distributed computing environment; however, integrity of data transmission in the distributed computing platform is hindered by a number of security issues. For instance, the botnet phenomenon is a prominent threat to Internet security, including the threat of malicious codes. The botnet phenomenon supports a wide range of criminal activities, including distributed denial of service (DDoS) attacks, click fraud, phishing, malware distribution, spam emails, and building machines for illegitimate exchange of information/materials. Therefore, it is imperative to design and develop a robust mechanism for improving the botnet detection, analysis, and removal process. Currently, botnet detection techniques have been reviewed in different ways; however, such studies are limited in scope and lack discussions on the latest botnet detection techniques. This paper presents a comprehensive review of the latest state-of-the-art techniques for botnet detection and figures out the trends of previous and current research. It provides a thematic taxonomy for the classification of botnet detection techniques and highlights the implications and critical aspects by qualitatively analyzing such techniques. Related to our comprehensive review, we highlight future directions for improving the schemes that broadly span the entire botnet detection research field and identify the persistent and prominent research challenges that remain open.Version
No full-text in the repositoryCitation
Karim A, Bin Salleh R, Shiraz M et al (2014) Botnet detection techniques: review, future trends, and issues. Journal of Zhejiang University-Science C-Computers & Electronics. 15(11): 943-983.Link to Version of Record
https://doi.org/10.1631/jzus.C1300242Type
Articleae974a485f413a2113503eed53cd6c53
https://doi.org/10.1631/jzus.C1300242